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BCFtools/RoH:一种用于从新一代测序数据中检测纯合性的隐马尔可夫模型方法。

BCFtools/RoH: a hidden Markov model approach for detecting autozygosity from next-generation sequencing data.

作者信息

Narasimhan Vagheesh, Danecek Petr, Scally Aylwyn, Xue Yali, Tyler-Smith Chris, Durbin Richard

机构信息

Wellcome Trust Sanger Institute, Hinxton and.

Department of Genetics, University of Cambridge, Cambridge, UK.

出版信息

Bioinformatics. 2016 Jun 1;32(11):1749-51. doi: 10.1093/bioinformatics/btw044. Epub 2016 Jan 30.


DOI:10.1093/bioinformatics/btw044
PMID:26826718
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4892413/
Abstract

UNLABELLED: Runs of homozygosity (RoHs) are genomic stretches of a diploid genome that show identical alleles on both chromosomes. Longer RoHs are unlikely to have arisen by chance but are likely to denote autozygosity, whereby both copies of the genome descend from the same recent ancestor. Early tools to detect RoH used genotype array data, but substantially more information is available from sequencing data. Here, we present and evaluate BCFtools/RoH, an extension to the BCFtools software package, that detects regions of autozygosity in sequencing data, in particular exome data, using a hidden Markov model. By applying it to simulated data and real data from the 1000 Genomes Project we estimate its accuracy and show that it has higher sensitivity and specificity than existing methods under a range of sequencing error rates and levels of autozygosity. AVAILABILITY AND IMPLEMENTATION: BCFtools/RoH and its associated binary/source files are freely available from https://github.com/samtools/BCFtools CONTACT: vn2@sanger.ac.uk or pd3@sanger.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

摘要

未标记:纯合性片段(RoHs)是二倍体基因组中的基因组片段,在两条染色体上显示相同的等位基因。较长的RoHs不太可能偶然出现,而可能表示纯合性,即基因组的两个拷贝都来自同一个近期祖先。早期检测RoH的工具使用基因型阵列数据,但测序数据可提供更多信息。在这里,我们展示并评估了BCFtools/RoH,它是BCFtools软件包的一个扩展,使用隐马尔可夫模型在测序数据(特别是外显子组数据)中检测纯合性区域。通过将其应用于模拟数据和千人基因组计划的真实数据,我们估计了它的准确性,并表明在一系列测序错误率和纯合性水平下,它比现有方法具有更高的灵敏度和特异性。 可用性和实现方式:BCFtools/RoH及其相关的二进制/源文件可从https://github.com/samtools/BCFtools免费获取。 联系方式:vn2@sanger.ac.uk或pd3@sanger.ac.uk 补充信息:补充数据可在《生物信息学》在线获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc0/4892413/bd1007243402/btw044f1p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc0/4892413/bd1007243402/btw044f1p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc0/4892413/bd1007243402/btw044f1p.jpg

相似文献

[1]
BCFtools/RoH: a hidden Markov model approach for detecting autozygosity from next-generation sequencing data.

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本文引用的文献

[1]
H3M2: detection of runs of homozygosity from whole-exome sequencing data.

Bioinformatics. 2014-6-24

[2]
An integrated map of genetic variation from 1,092 human genomes.

Nature. 2012-11-1

[3]
Detecting autozygosity through runs of homozygosity: a comparison of three autozygosity detection algorithms.

BMC Genomics. 2011-9-23

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Nature. 2010-10-28

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Am J Hum Genet. 2010-3-18

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Genome Res. 2009-2

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Am J Hum Genet. 2007-9

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